Session 10 Machine Learning: Text classification - Unsupervised (1)

Note: The following slides (Session 10) are material from a guest lecture presented by Camille Landesvatter (MZES Website).

  • Learning outcomes:
    • learn basic concepts of Natural Language Processing (NLP)
    • become familiar with a typical (R-)workflow for text analysis
    • overview machine learning approaches for text data (supervised & unsupervised)
    • Lab:
      • structural topic model in R (unsupervised ML)